There are more and more ways for crowdsourcing clinical questions, and the newest addition to the family of web tools and services is Figure 1, a photo sharing site for healthcare professionals. Registered physicians can share images, learn from others and bookmark useful cases.
I’m not sure this is what the medical community requires right now, but I’m always curious about further developments.
According to the co-founder, Joshua Landy, MD:
“I developed Figure 1 because I wanted a safe way to share medical images with the medical community, while protecting patients’ privacy.”
I’m still trying to find ways to use the really professional network, Google+, in medicine and I asked my community a few days ago about that:
I haven’t asked you about that for a while, but how have your habits been changing in the last few weeks on Google+? Do you use it more than Facebook? For me, it seemed to be a fantastic professional network, but still have many more peers on Twitter and Facebook. What to do?
I got some interesting opinions and ideas, but a French colleague told me French doctors actually perform case presentations in private ways. They upload information about the case, discuss it with other peers and get to a final diagnosis. Based on the very simple privacy settings of Google+, it can be useful for such purposes. Anyone else with similar experience?
As I’ve been an administrator of Wikipedia, it’s really important for me to persuade more and more professionals to edit Wikipedia. A new paper published in PLoS Computational Biology seems to be a very helpful first step for those who are interested in editing biomedical content in the biggest encyclopaedia.
Ten Simple Rules for Editing Wikipedia
- Rule 1: Register an Account
- Rule 2: Learn the Five Pillars
- Rule 3: Be Bold, but Not Reckless
- Rule 4: Know Your Audience
- Rule 5: Do Not Infringe Copyright
- Rule 6: Cite, Cite, Cite
- Rule 7: Avoid Shameless Self-Promotion
- Rule 8: Share Your Expertise, but Don’t Argue from Authority
- Rule 9: Write Neutrally and with Due Weight
- Rule 10: Ask for Help
I have some other tips dedicated to the biomedical entries.
- Focus on the Medical Collaboration of the Month if you cannot choose which entry to work on.
- Defend entries that would be deleted
- There are entries needing expert attention
- Requested articles in medicine
- Expand medical stub entries
- Contribute to the assessment of medical entries
- Work on the most visited Medical Portal
- Find collaborators or other projects on WikiProject Medicine
Almost two years ago, I asked my Friendfeed community a question:
“What is your favourite blog story (that happened to you because you’re blogging)? I would like to share the best stories with students at the Medicince 2.0 credit course.”
I received plenty of answers and later this open Google Document was created for a similar purpose: how Friendfeed helped your career. A few examples:
- Advice on new lab material purchase
- Request for other Life Scientists to review an NIH grant prior to submission.
- Extraction of the information about the proteins in wikipedia. Potential paper to come.
- Andy started an entry on Wikipedia for Open Notebook Science and several people added content and support to have it accepted by editors
Feel free to share Your story!
I just joined an initiative on Wikipedia which features Google and the medical editors on Wikipedia. WikiProject Medicine editors and Google reviewers work together on articles within Wikipedia:WikiProject Medicine.
Initiated at Google.org and then announced at Wikipedia talk:WikiProject Medicine#Announcement to WikiProject Medicine community prior to trial editorial review, this collaboration is intended as an exploration of active cooperation between professional medical editors and wikipedians to further improve the quality of articles. Work began with the identification of a short list of articles for review, selected as a cross-section of medicine-related topics. Each article on the list now has an assessed “Class” and “Importance”, harvested from its talk-page banner, reflecting Wikipedians’ initial assessment of their state.
While I’m not really sure I understand why it’s beneficial for Google, this is a great project which I’m gladly participating in.
If you remember the SETI project, you won’t be surprised that the Foldit project is a huge success. Foldit is an experimental video game about protein folding which helps solve problems that computers cannot solve that efficiently.
As described above, knowing the structure of a protein is key to understanding how it works and to targeting it with drugs. A small proteins can consist of 100 amino acids, while some human proteins can be huge (1000 amino acids). The number of different ways even a small protein can fold is astronomical because there are so many degrees of freedom. Figuring out which of the many, many possible structures is the best one is regarded as one of the hardest problems in biology today and current methods take a lot of money and time, even for computers. Foldit attempts to predict the structure of a protein by taking advantage of humans’ puzzle-solving intuitions and having people play competitively to fold the best proteins.
And they plan to publish the results with a cover which includes 75,000 provile images:
In the social media era, when there are so many opportunities for collaborations, we just had to wait until pharma companies realize that and find some ways to work together for better drugs or methods. A recent Nature Biotechnology article written by Stephen Strauss features some major steps in this area.
On May 19, two large pharmaceutical companies participated in the unprecedented deposition of hundreds of thousands of potential leads for new malaria drugs into an open source database. The two companies, London-based GlaxoSmithKline (GSK) and Novartis of Basel, together with the St. Jude Children’s Research Hospital in Memphis, Tennessee, submitted the chemical structures of 328,100 compounds active against the malaria parasite Plasmodium falciparum to a European Bioinformatics Institute ChEMBL Neglected Tropical Disease archive. This willingness to cooperate in nonproprietary collaborations goes beyond diseases neglected by commercial developers to other aspects of drug discovery research. A recent flurry of open source collaborations have sprung up recently aimed at extracting value out of precompetitive information. Merck, of Whitehouse Station, New Jersey, signed up with Sage Bionetworks, a Seattle-based nonprofit collaborative information platform run by former Merck scientists and executives, and New York-based Pfizer has entered into a similar arrangement. These and other deals mark the beginning of a radical reconfiguration of the initial stages of the drug discovery process that were traditionally carried out within companies.
And click here to see a table containing selected open source collaborations involving pharma.